Map-reduce which is a distributed processing technique has been used in recent years as a technique for processing large amount of data. Map-reduce is a distributed processing technique in which processing of data is performed separately in two stages which are map processing and reduce processing. In map-reduce, data accumulated in a database at predetermined intervals is divided into a plurality of pieces of data. Further, each of a plurality of nodes executes map processing in which certain processing is performed with respect to the divided data. Then, at least any node among a plurality of nodes executes reduce processing for acquiring a processing result of the whole data, with respect to a processing result of the map processing.
As a related technique, a technique which applies map-reduce to information, in which a set of interests of each of a plurality of users is stored, so as to enable clustering of the users has been disclosed.
As related art, Japanese National Publication of International Patent Application No. 2009-505290 has been disclosed, for example.